Genetic risk model for in-stent restenosis of second-and third-generation drug-eluting stents

A systematic review and bioinformatic study on clinical, paraclinical, and genetic factors predisposing to stent restenosis following percutaneous coronary intervention

BACKGROUND

Stent restenosis is a relatively common phenomenon among patients with coronary heart disease undergoing percutaneous coronary intervention (PCI). It seems that a set of clinical, laboratory, and even genetic factors make people susceptible to such a phenomenon and in fact, this is multi-factorial. We aimed to first determine the underlying clinical and laboratory risk factors for the occurrence of stent re-stenosis after PCI based on a systematic review study, and after that, through a bioinformatics study, to evaluate the related genes and microRNAs with the occurrence of stent re-stenosis.

MAIN TEXT

In the first step, the manuscript databases including Medline, Web of Knowledge, Google Scholar, Scopus, and Cochrane were deeply searched by the two blinded investigators for all eligible studies based on the considered keywords to introduce clinical and laboratory determinants of stent re-stenosis. In the bioinformatic phase, and following a review of the literature to identify genes and microRNAs involved in restenosis, the interaction of each gene with other genes associated with stent re-stenosis was determined by GeneMANIA network analysis and Cytoscape software. Overall, 67 articles (including 40,789 patients) on clinical and biochemical predictors for stent restenosis and 25 articles on genetic determinants of this event were eligible for the final analysis. The predictors for this event were categorized into four subgroups patient-based parameters including traditional cardiovascular risk profiles, stent-based parameters including type and diametric characteristics of the stents used, coronary lesion-based parameters including several two target lesions and coronary involvement severity and laboratory-based parameters particularly related to activation of inflammatory processes. In the bioinformatic phase, we uncovered 42 genes that have been described to be involved in such a phenomenon considering a special position for genes encoding inflammatory cytokines. Also, 12 microRNAs have been pointed to be involved in targeting genes involved in stent re-stenosis.

CONCLUSIONS

The incidence of stent re-stenosis will be the result of a complex interaction of clinical risk factors, laboratory factors mostly related to the activation of inflammatory processes, and a complex network of gene-to-gene interactions.

Application of genetic risk score for in-stent restenosis of second- and third-generation drug-eluting stents in geriatric patients

BACKGROUND

The second-and third-generation drug-eluting stents (DESs) in-stent restenosis (ISR) genetic risk score (GRS) model has been previously validated. However, the model has not been validated in geriatric patients. Therefore, we conducted this study to test the feasibility of the DES-ISR GRS model in geriatric patients with coronary artery disease (CAD) in Taiwan.

METHODS

We conducted a retrospective, single-center cohort study and included geriatric patients (age ≥ 65 years) with CAD and second-or third-generation DES(s) deployment. Patients undergoing maintenance dialysis were excluded. ISR was defined as ≥ 50% luminal narrowing on the follow-up coronary arteriography. The DES-ISR GRS model included five selected exonic single-nucleotide polymorphisms (SNPs): CAMLG, GALNT2, C11orf84, THOC5, and SAMD11. The GRS was defined as the sum of the five selected SNPs for the risk allele.

RESULTS

We enrolled 298 geriatric patients from January 2010 and December 2019 in this study. After propensity score matching, there were 192 geriatric patients with CAD in the final analysis, of which 32 patients had ISR. Patients were divided into two groups based on their GRS values: low (0-2) and high (≥ 3) GRS. A high GRS was significantly associated with DES-ISR in geriatric patients.

CONCLUSION

Those geriatric patients with a high GRS had significantly higher second-or third-generation DES ISR rates. The five SNP-derived DES-ISR GRS model could provide genetic information for interventional cardiologists to treat geriatric patients with CAD.

TRIAL REGISTRATION

The primary study protocol was registered with clinicaltrials.org. with registration number: NCT03877614; on March 15, 2019. ( http://clinicaltrials.gov/ct2/show/NCT03877614 ).

Genetic Variants in PHACTR1 & LPL Mediate Restenosis Risk in Coronary Artery Patients

Background and Objective

Coronary artery disease (CAD) is a major cause of death worldwide. Revascularization via stent placement or coronary artery bypass grafting (CABG) are standard treatments for CAD. Despite a high success rate, these approaches are associated with long-term failure due to restenosis. Risk factors associated with restenosis were investigated using a case-control association study design.

Methods

Five thousand two hundred and forty-two patients were enrolled in this study and were assigned as follows: Stenosis Group: 3570 patients with CAD >50% without a prior stent or CABG (1394 genotyped), and Restenosis Group: 1672 patients with CAD >50% and prior stent deployment or CABG (705 genotyped). Binomial regression models were applied to investigate the association of restenosis with diabetes, hypertension, and dyslipidemia. The genetic association with restenosis was conducted using PLINK 1.9.

Results

Dyslipidemia is a major risk factor (Odds Ratio (OR) = 2.14, P-value <0.0001) for restenosis particularly among men (OR = 2.32, P < 0.0001), while type 2 diabetes (T2D) was associated with an increased risk of restenosis in women (OR = 1.36, P = 0.01). The rs9349379 (PHACTR1) and rs264 (LPL) were associated with an increased risk of restenosis in our patients. PHACTR1 variant was associated with increased risk of restenosis mainly in women and in diabetic patients, while the LPL variant was associated with increased risk of restenosis in men.

Conclusion

The rs9349379 in PHACTR1 gene is significantly associated with restenosis, this association is more pronounced in women and in diabetic patients. The rs264 in LPL gene was associated with increased risk of restenosis in male patients.

Bioimpedance Sensing of Implanted Stent Occlusions: Smart Stent

Coronary artery disease is one of the most common diseases in developed countries and affects a large part of the population of developing countries. Preventing restenosis in patients with implanted stents is an important current medical problem. The purpose of this work is to analyse the viability of bioimpedance sensing to detect the formation of atheromatous plaque in an implantable stent. Simulations in COMSOL Multiphysics were performed to analyse the performance of the proposed bioimpedance sensing system, based on the Sheffield technique. Both non-pathological and pathological models (with atheromatous plaque), including the flow of blood were considered. Simulations with the non-pathological model showed a homogeneous distribution of the measured current intensity in the different electrodes, for every configuration. On the other hand, simulations with the pathological model showed a significant decrease of the measured current intensity in the electrodes close to the simulated atheromatous plaque. The presence of the atheromatous plaque can, therefore, be detected by the system with a simple algorithm, avoiding the full reconstruction of the image and the subsequent computational processing requirements.

Role of Glycosylation in Vascular Calcification

Glycosylation is an important step in post-translational protein modification. Altered glycosylation results in an abnormality that causes diseases such as malignancy and cardiovascular diseases. Recent emerging evidence highlights the importance of glycosylation in vascular calcification. Two major types of glycosylation, N-glycosylation and O-glycosylation, are involved in vascular calcification. Other glycosylation mechanisms, which polymerize the glycosaminoglycan (GAG) chain onto protein, resulting in proteoglycan (PG), also have an impact on vascular calcification. This paper discusses the role of glycosylation in vascular calcification.